[DOC] Complete Related Software documentation page

.all-contributorsrc

@@ -256,6 +256,14 @@
         "code",
         "bug"
       ]
-    },
+    {
+      "login": "maniktyagi04",
+      "name": "Manik Tyagi",
+      "avatar_url": "https://avatars.githubusercontent.com/u/74643036?v=4",
+      "profile": "https://github.com/maniktyagi04",
+      "contributions": [
+        "doc"
+      ]
+    }
   ]
 }

docs/source/related_software.rst

@@ -4,4 +4,54 @@
 Related Software
 ================
 
-TODO
+The following is a curated list of software packages related to ``skpro``
+in the probabilistic prediction and scientific Python ecosystem.
+
+Probabilistic Prediction & Forecasting
+---------------------------------------
+
+`sktime <https://www.sktime.net>`_
+    A unified framework for time series machine learning in Python.
+    ``skpro`` is maintained by the same community and integrates with ``sktime``
+    to enable probabilistic forecasting pipelines: an ``sktime`` probabilistic
+    forecaster can be built from an ``skpro`` probabilistic regressor.
+
+`ngboost <https://stanfordmlgroup.github.io/projects/ngboost/>`_
+    Natural Gradient Boosting for probabilistic prediction.
+    ``skpro`` provides a native interface to ``ngboost`` estimators via the
+    ``NGBoostRegressor`` and ``NGBoostSurvival`` classes.
+
+`cyclic-boosting <https://cyclic-boosting.readthedocs.io>`_
+    A Python package for probabilistic prediction using cyclic boosting algorithms.
+    ``skpro`` provides a native interface to ``cyclic-boosting`` estimators.
+
+Uncertainty Quantification & Conformal Prediction
+--------------------------------------------------
+
+`MAPIE <https://mapie.readthedocs.io>`_
+    Model Agnostic Prediction Interval Estimator.
+    A library for uncertainty quantification via conformal prediction, compatible
+    with ``scikit-learn``. ``skpro`` can interface with MAPIE for interval
+    and quantile prediction.
+
+Machine Learning Foundations
+-----------------------------
+
+`scikit-learn <https://scikit-learn.org>`_
+    The standard Python machine learning library.
+    ``skpro`` is fully ``scikit-learn``-compatible and ``scikit-base``-compliant,
+    extending ``scikit-learn`` regressors with probabilistic prediction capabilities.
+
+Survival & Time-to-Event Analysis
+-----------------------------------
+
+`lifelines <https://lifelines.readthedocs.io>`_
+    A complete survival analysis library for Python, implementing a wide range
+    of parametric and non-parametric survival models.
+
+Probabilistic Programming
+--------------------------
+
+`pymc <https://www.pymc.io>`_
+    A probabilistic programming library in Python for Bayesian statistical modeling
+    and inference using Markov Chain Monte Carlo (MCMC) and variational inference.